---
title: Agent with Storage
---

## Code

```python cookbook/models/cerebras_openai/knowledge.py

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.cerebras import CerebrasOpenAI
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

knowledge = Knowledge(
    vector_db=PgVector(table_name="recipes", db_url=db_url),
)
# Add content to the knowledge
knowledge.add_content(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"
)

agent = Agent(
    model=CerebrasOpenAI(id="llama-4-scout-17b-16e-instruct"), knowledge=knowledge
)
agent.print_response("How to make Thai curry?", markdown=True)
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Set your API key">
    ```bash
    export CEREBRAS_API_KEY=xxx
    ```
  </Step>

  <Step title="Install libraries">
    ```bash
    pip install -U openai ddgs sqlalchemy pgvector pypdf agno
    ```
  </Step>

  <Step title="Run Agent">
    <CodeGroup>
    ```bash Mac
    python cookbook/models/cerebras_openai/knowledge.py
    ```

    ```bash Windows
    python cookbook/models/cerebras_openai/knowledge.py
    ```
    </CodeGroup>
  </Step>
</Steps>